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LipoSVM: Prediction of Lysine Lipoylation in Proteins based on the Support Vector Machine

文献类型：期刊论文

作者Wu, Meiqi1; Lu, Pengchao2; Yang, Yingxi3; Liu, Liwen1; Wang, Hui4; Xu, Yan1; Chu, Jixun1
刊名CURRENT GENOMICS
出版日期2019
卷号20期号:5页码:362-370
关键词Lysine lipoylation prediction amino acids support vector machine post-translational modifications scoring matrix
ISSN号1389-2029
DOI10.2174/1389202919666191014092843
英文摘要Background: Lysine lipoylation which is a rare and highly conserved post-translational modification of proteins has been considered as one of the most important processes in the biological field. To obtain a comprehensive understanding of regulatory mechanism of lysine lipoylation, the key is to identify lysine lipoylated sites. The experimental methods are expensive and laborious. Due to the high cost and complexity of experimental methods, it is urgent to develop computational ways to predict lipoylation sites. Methodology: In this work, a predictor named LipoSVM is developed to accurately predict lipoylation sites. To overcome the problem of an unbalanced sample, synthetic minority over-sampling technique (SMOTE) is utilized to balance negative and positive samples. Furthermore, different ratios of positive and negative samples are chosen as training sets. Results: By comparing five different encoding schemes and five classification algorithms, LipoSVM is constructed finally by using a training set with positive and negative sample ratio of 1:1, combining with position-specific scoring matrix and support vector machine. The best performance achieves an accuracy of 99.98% and AUC 0.9996 in 10-fold cross-validation. The AUC of independent test set reaches 0.9997, which demonstrates the robustness of LipoSVM. The analysis between lysine lipoylation and non-lipoylation fragments shows significant statistical differences. Conclusion: A good predictor for lysine lipoylation is built based on position-specific scoring matrix and support vector machine. Meanwhile, an online webserver LipoSVM can be freely downloaded from https://github.com/stars20180811/LipoSVM.
资助项目Natural Science Foundation of China[11671032]
WOS研究方向Biochemistry & Molecular Biology ; Genetics & Heredity
语种英语
WOS记录号WOS:000500783300006
出版者BENTHAM SCIENCE PUBL LTD
源URL[http://119.78.100.204/handle/2XEOYT63/14934]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chu, Jixun
作者单位1.Univ Sci & Technol Beijing, Dept Appl Math, Beijing 100083, Peoples R China
2.China Petr Pipeline Engn Co Ltd, Equipment Leasing Co, Langfang City 065000, Hebei, Peoples R China
3.Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Hong Kong, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Meiqi,Lu, Pengchao,Yang, Yingxi,et al. LipoSVM: Prediction of Lysine Lipoylation in Proteins based on the Support Vector Machine[J]. CURRENT GENOMICS,2019,20(5):362-370.
APA Wu, Meiqi.,Lu, Pengchao.,Yang, Yingxi.,Liu, Liwen.,Wang, Hui.,...&Chu, Jixun.(2019).LipoSVM: Prediction of Lysine Lipoylation in Proteins based on the Support Vector Machine.CURRENT GENOMICS,20(5),362-370.
MLA Wu, Meiqi,et al."LipoSVM: Prediction of Lysine Lipoylation in Proteins based on the Support Vector Machine".CURRENT GENOMICS 20.5(2019):362-370.

入库方式： OAI收割

来源：计算技术研究所

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